Batch Information

Batch B002
N Samples 2
N Pools 1
N Wells 11
Batch Control TRUE
B002-P1 Samples IMM19_698, PB00004-01, PB00006-01

QC Results Summary

Category Results Description
Well Sequencing and Alignment Warning
Cell Hashing Pass
Cell Labeling Pass
Control Sample Pass

Summary Details

Well Sequencing and Alignment

The following metrics summarize the sequencing and alignment by 10x well prior to un-hashing and hash-based cell filtering.

Detailed Well Summary

Spec Median_Range Inter_Well_CV Comments Plot
estimated_number_of_cells 30811 (21882-33097) 10.0% Fail: message

Plot
fraction_reads_in_cells 94.0 (93.0-94.9) 0.6%

Plot
mean_reads_per_cell 30832 (26087-43885) 15.0%

Plot
median_genes_per_cell 1593 (1500-1796) 4.9% Warning: message

Plot
median_umi_counts_per_cell 5219 (4848-6153) 6.8%

Plot
number_of_reads 946975235 (791967202-1088565134) 7.5%

Plot
q30_bases_in_barcode 96.2 (96.1-96.2) 0.0%

Plot
q30_bases_in_rna_read 94.3 (93.9-94.7) 0.3%

Plot
q30_bases_in_sample_index 94.4 (92.8-95.2) 0.9%

Plot
q30_bases_in_umi 96.0 (96.0-96.1) 0.0%

Plot
reads_mapped_antisense_to_gene 2.0 (1.8-2.1) 6.2%

Plot
reads_mapped_confidently_to_exonic_regions 63.0 (60.1-65.6) 2.7%

Plot
reads_mapped_confidently_to_genome 89.9 (88.3-91.4) 0.9%

Plot
reads_mapped_confidently_to_intergenic_regions 4.0 (3.8-4.2) 3.2%

Plot
reads_mapped_confidently_to_intronic_regions 22.9 (21.1-24.8) 4.9% Warning: message

Plot
reads_mapped_confidently_to_transcriptome 58.3 (55.4-61.1) 3.1%

Plot
reads_mapped_to_genome 94.2 (92.9-95.5) 0.7%

Plot
sequencing_saturation 60.9 (56.0-65.5) 4.1% Warning: message

Plot
total_genes_detected 24330 (24169-24554) 0.5% Warning: message

Plot
valid_barcodes 97.3 (97.2-97.4) 0.1%

Plot

Cell Hashing and Sample Quality Metrics

Specification Value Comments
x x
x x
x x Warning: message
x x Fail: mesage
x x

Pool-based Summary

hto_category pool_id n_cells median_reads median_umis median_genes
doublet B002-P1 76166 20637.0 7890 2209.5
multiplet B002-P1 19143 30170.0 11515 2927.0
no_hash B002-P1 6969 8668.0 3387 1174.0
singlet B002-P1 38770 12979.5 4889 1490.0
doublet B002-P2 72164 22688.5 7413 2076.0
multiplet B002-P2 16543 35190.0 11448 2831.0
no_hash B002-P2 3908 4182.0 1732 566.5

Well-Based Summary

## `summarise()` regrouping output by 'hto_barcode', 'pbmc_sample_id', 'sample_hto' (override with `.groups` argument)
pool_id well_id n_cells median_reads median_umis median_genes
B002-P1 B002-P1C1W1 8721 24641.0 8200.0 2307.0
B002-P1 B002-P1C1W3 13989 14785.0 5920.0 1815.0
B002-P1 B002-P1C1W4 12608 15342.5 6565.5 1964.0
B002-P1 B002-P1C1W5 12351 18376.0 7195.0 2075.0
B002-P1 B002-P1C1W6 13742 18716.0 6673.0 2000.5
B002-P1 B002-P1C1W7 14609 15804.0 6163.0 1890.0
B002-P1 B002-P1C1W8 13344 16953.5 6399.0 1901.0
B002-P1 B002-P1C2W1 12414 19354.5 7292.5 2096.5
B002-P1 B002-P1C2W2 13443 18261.0 6685.0 1944.0
B002-P1 B002-P1C2W3 13556 16417.0 6203.0 1862.0
B002-P1 B002-P1C2W4 12271 18944.0 6938.0 2014.0
B002-P2 B002-P2C2W5 8082 22815.0 8254.0 2280.0
B002-P2 B002-P2C2W6 8323 23584.0 8009.0 2224.0
B002-P2 B002-P2C2W7 7329 26043.0 8329.0 2291.0
B002-P2 B002-P2C2W8 7131 26261.0 8463.0 2308.0
B002-P2 B002-P2C3W1 7092 21886.5 7456.0 2062.0
B002-P2 B002-P2C3W2 7991 25453.0 8147.0 2194.0
B002-P2 B002-P2C3W3 8105 23396.0 7420.0 2060.0
B002-P2 B002-P2C3W4 7715 21072.0 7047.0 1991.0
B002-P2 B002-P2C3W5 7968 23740.0 7718.0 2117.5
B002-P2 B002-P2C3W6 9040 22597.5 7325.5 2063.0
B002-P2 B002-P2C3W7 7427 26055.0 7729.0 2129.0
B002-P2 B002-P2C3W8 6412 24037.0 7768.0 2119.0

HTO Assignment Cutoffs

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HTO Category Counts by Well

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HTO Category Fraction by Well

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Singlet Summaries (hash-based)

HTO Barcode Count per Well Plot

HTO Barcode Fraction per Well Plot

Well Count per HTO Barcode Plot

Well Fraction per HTO Barcode Plot

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Counts by HTO Category and Barcode
## Warning: Removed 2 rows containing non-finite values (stat_ydensity).

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## Warning: Removed 1 rows containing non-finite values (stat_ydensity).

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## Warning: Non-unique features (rownames) present in the input matrix, making
## unique

Batch-level UMAP using 4 principal components (19.4% explained variance).

## Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
## To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
## This message will be shown once per session

Data Quality UMAP

Cell Labeling

Specification Value Comments
x x
x x
x x Warning: message
x x Fail: mesage
x x

Seurat Labeling Scores

UMAP for all cells

## Warning: Aspect ratios aren't yet implemented, but you can manually set a
## suitable height/width

## Warning: Aspect ratios aren't yet implemented, but you can manually set a
## suitable height/width

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UMAP for cells with Fraction Mitochondrial UMI0.05

Removed 7159 cells (18.5%)

Marker Visualization

Plotting cells with low fraction mitochondrial counts (<{r fct_mito_umi_threshold)})

Leukopak Control

Specification Value Comments
x x
x x
x x Warning: message
x x Fail: mesage
x x 

## Warning: Non-unique features (rownames) present in the input matrix, making
## unique

Batch-level UMAP using 5 principal components (15.8% explained variance).

Session Information

Files Analyzed:

## [1] "B002-P1_IMM19-698_labeled.h5"  "B002-P1_PB00004-01_labeled.h5"
## [3] "B002-P1_PB00006-01_labeled.h5"
##  [1] "B002-P1C1W1_hto_processing_metrics.json"
##  [2] "B002-P1C1W2_hto_processing_metrics.json"
##  [3] "B002-P1C1W3_hto_processing_metrics.json"
##  [4] "B002-P1C1W4_hto_processing_metrics.json"
##  [5] "B002-P1C1W5_hto_processing_metrics.json"
##  [6] "B002-P1C1W6_hto_processing_metrics.json"
##  [7] "B002-P1C1W7_hto_processing_metrics.json"
##  [8] "B002-P1C1W8_hto_processing_metrics.json"
##  [9] "B002-P1C2W1_hto_processing_metrics.json"
## [10] "B002-P1C2W2_hto_processing_metrics.json"
## [11] "B002-P1C2W3_hto_processing_metrics.json"
## [12] "B002-P1C2W4_hto_processing_metrics.json"
## [13] "B002-P2C2W5_hto_processing_metrics.json"
## [14] "B002-P2C2W6_hto_processing_metrics.json"
## [15] "B002-P2C2W7_hto_processing_metrics.json"
## [16] "B002-P2C2W8_hto_processing_metrics.json"
## [17] "B002-P2C3W1_hto_processing_metrics.json"
## [18] "B002-P2C3W2_hto_processing_metrics.json"
## [19] "B002-P2C3W3_hto_processing_metrics.json"
## [20] "B002-P2C3W4_hto_processing_metrics.json"
## [21] "B002-P2C3W5_hto_processing_metrics.json"
## [22] "B002-P2C3W6_hto_processing_metrics.json"
## [23] "B002-P2C3W7_hto_processing_metrics.json"
## [24] "B002-P2C3W8_hto_processing_metrics.json"
## [1] "B002-P1C1W1-RNA_multiplet.h5" "B002-P2_multiplet.h5"

Session Info:

## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] future.apply_1.6.0 future_1.19.1      inflection_1.3.5   Seurat_3.9.9.9010 
##  [5] tidyr_1.1.2        immutils_0.0.2     plotly_4.9.2.1     gt_0.2.2          
##  [9] cowplot_1.1.0      dplyr_1.0.2        ggplot2_3.3.2      HTOparser_1.0.12  
## [13] H5weaver_1.0.17    rlang_0.4.8        data.table_1.13.2  rhdf5_2.32.4      
## [17] Matrix_1.2-18     
## 
## loaded via a namespace (and not attached):
##   [1] Rtsne_0.15            colorspace_1.4-1      deldir_0.1-29        
##   [4] ellipsis_0.3.1        ggridges_0.5.2        spatstat.data_1.4-3  
##   [7] farver_2.0.3          leiden_0.3.3          listenv_0.8.0        
##  [10] ggrepel_0.8.2         RSpectra_0.16-0       codetools_0.2-16     
##  [13] splines_4.0.3         knitr_1.30            polyclip_1.10-0      
##  [16] jsonlite_1.7.1        ica_1.0-2             cluster_2.1.0        
##  [19] png_0.1-7             uwot_0.1.9.9000       shiny_1.5.0          
##  [22] sctransform_0.3.1     compiler_4.0.3        httr_1.4.2           
##  [25] backports_1.1.10      assertthat_0.2.1      fastmap_1.0.1        
##  [28] lazyeval_0.2.2        later_1.1.0.1         htmltools_0.5.0      
##  [31] tools_4.0.3           rsvd_1.0.3            igraph_1.2.6         
##  [34] gtable_0.3.0          glue_1.4.2            RANN_2.6.1           
##  [37] reshape2_1.4.4        Rcpp_1.0.5            spatstat_1.64-1      
##  [40] vctrs_0.3.4           nlme_3.1-149          crosstalk_1.1.0.1    
##  [43] lmtest_0.9-38         xfun_0.18             stringr_1.4.0        
##  [46] globals_0.13.1        mime_0.9              miniUI_0.1.1.1       
##  [49] lifecycle_0.2.0       irlba_2.3.3           goftest_1.2-2        
##  [52] MASS_7.3-53           zoo_1.8-8             scales_1.1.1         
##  [55] promises_1.1.1        spatstat.utils_1.17-0 parallel_4.0.3       
##  [58] RColorBrewer_1.1-2    yaml_2.2.1            reticulate_1.16      
##  [61] pbapply_1.4-3         gridExtra_2.3         sass_0.2.0           
##  [64] rpart_4.1-15          stringi_1.5.3         checkmate_2.0.0      
##  [67] commonmark_1.7        pkgconfig_2.0.3       matrixStats_0.57.0   
##  [70] evaluate_0.14         lattice_0.20-41       ROCR_1.0-11          
##  [73] purrr_0.3.4           tensor_1.5            Rhdf5lib_1.10.1      
##  [76] labeling_0.4.2        patchwork_1.0.1       htmlwidgets_1.5.2    
##  [79] tidyselect_1.1.0      RcppAnnoy_0.0.16      plyr_1.8.6           
##  [82] magrittr_1.5          R6_2.4.1              generics_0.0.2       
##  [85] pillar_1.4.6          withr_2.3.0           mgcv_1.8-33          
##  [88] fitdistrplus_1.1-1    survival_3.2-7        abind_1.4-5          
##  [91] tibble_3.0.4          crayon_1.3.4          KernSmooth_2.23-17   
##  [94] rmarkdown_2.4         grid_4.0.3            digest_0.6.26        
##  [97] xtable_1.8-4          httpuv_1.5.4          munsell_0.5.0        
## [100] viridisLite_0.3.0

Total time elapsed

## [1] "Elapsed Time: 4.698 mins"

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